Metabolites are sensitive to genetic and environmental factors, and as a result are good indicators of disease or phenotype. The overall goal of metabolomics is the measurement of all metabolites associated with a specific disease, treatment, genotype, etc. Combined with other `omics, metabolomics is becoming indispensable in systems biology studies, precision medicine, food and agricultural industry, and cell-based pharmaceuticals. The major difficulty in metabolomics is the reliable and reproducible identification and quantification of metabolites. Analytical technologies such as NMR and LC-MS can provide hundreds to tens of thousands of peaks from metabolomics samples, but efficiently quantifying these peaks and confidently assigning them to real metabolites remains a significant challenge. The standard approach to NMR metabolomics is to detect 1H, because it is both abundant and sensitive. The problem with 1H NMR is that peaks are often overlapped, making reliable identification and quantification difficult. We have developed new approaches to metabolomics using 13C detection by NMR, both at natural abundance and with isotopic enrichment, to exploit the advantages of reduced peak overlap due to large spectral dispersion of 13C and more robust database matching of chemical shifts to metabolites. The primary limitation of 13C-based NMR metabolomics is sensitivity. We propose to develop a 5-mm 13C-optimized 800 MHz NMR probe made from high-temperature superconductors (HTS) that will improve the sensitivity for metabolomics samples by at least a factor of 3 beyond what is currently available. This sensitivity increase will reduce measurement times by at least a factor of 9x or it will allow us to detect metabolites at 3-fold lower concentrations. These improvements will be coupled with new acquisition methods using 2 NMR receivers and will be implemented on a new 800 MHz NMR spectrometer for enhanced sensitivity and throughput. Based on the target value for 13C signal-to- noise of 9000:1 for the ASTM standard, we expect to be able to fully quantify and identify up to around 130 metabolites in a biofluid like human serum in about 2 hours. We are also developing methods to fractionate and concentrate samples using HPLC and solid phase extraction (SPE), and this technology will allow us to also measure mass spectrometry data on the same samples. We should be able to characterize over 300 metabolites with a 5x SPE concentration, or 450 metabolites with a 10x SPE. This project will greatly improve the reproducibility, reliability, and biological information content of metabolomics. We will disseminate the technology through commercialization or by making the drawings available to interested investigators.
Aim 1) Develop an 18.8 T 5-mm 13C-optimized HTS probe that will be installed on a Bruker Avance III HD NMR spectrometer in the Complex Carbohydrate Research Center (CCRC) at the University of Georgia.
Aim 2) Develop new metabolomics applications using 2 receivers with quantitative 13C 1D and simultaneous 1H 2D NMR experiments. LC-SPE will allow concentration and coupling with MS.
Metabolites are sensitive to genetic and environmental factors, and as a result are good indicators of disease. The overall goal of metabolomics is the measurement and quantification of all metabolites associated with a specific disease or treatment, but the major difficulty in metabolomics is the identification and quantification of metabolites. We will develop new NMR technology and metabolomics protocols that will significantly improve our ability to both identify and quantify hundreds of metabolites and thus extract important biological information from analytical data. This will substantially improve the reproducibility and overall biological impact of metabolomics.
